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图像处理需要联网clawhub未标认证来源可访问clear审计通过

image-generation图像生成

Agent Skill

用于辅助图像生成、图片编辑、视觉素材处理或图像模型工作流。它适合让 Agent 根据文本生成图片、处理背景、整理视觉提示词或调用相关图像工具。使用时需要确认输入图片、版权来源、输出格式和模型限制;涉及人物、品牌、商品或公开展示素材时,应额外核对授权、真实性和内容合规边界。

总安装

222,557

周安装

9,560

GitHub Stars

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下载量

78,010
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:image-generation(图像生成)
来源仓库:https://github.com/ivangdavila/image-generation
安装命令:
openclaw skills install image-generation
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install image-generation

简介

使用 GPT Image、Gemini Nano Banana、FLUX、Imagen 和顶级提供商,使用即时工程、风格控制和智能编辑来创建 AI 图像。

SKILL.md

name
AI Image Generation
slug
image-generation
version
1.0.3
homepage
https://clawic.com/skills/image-generation
description
Create AI images with GPT Image, Gemini Nano Banana, FLUX, Imagen, and top providers using prompt engineering, style control, and smart editing.
changelog
Updated for 2026 with benchmark-backed model selection and clearer guidance for modern image generation stacks.
metadata
{"clawdbot":{"emoji":"🎨","requires":{"bins":[],"env.optional":["OPENAI_API_KEY","GEMINI_API_KEY","BFL_API_KEY","GOOGLE_CLOUD_PROJECT","REPLICATE_API_TOKEN","LEONARDO_API_KEY","IDEOGRAM_API_KEY"],"config":["~/image-generation/"]},"os":["linux","darwin","win32"]}}

Setup

On first use, read setup.md.

When to Use

User needs AI-generated visuals, edits, or consistent image sets. Use this skill to pick the right model, write stronger prompts, and avoid outdated model choices.

Architecture

User preferences persist in ~/image-generation/. See memory-template.md for setup.

~/image-generation/
├── memory.md      # Preferred providers, project context, winning recipes
└── history.md     # Optional generation log

Quick Reference

TopicFile
Initial setupsetup.md
Memory templatememory-template.md
Migration guidemigration.md
Benchmark snapshotsbenchmarks-2026.md
Prompt techniquesprompting.md
API handlingapi-patterns.md
GPT Image (OpenAI)gpt-image.md
Gemini and Imagen (Google)gemini.md
FLUX (Black Forest Labs)flux.md
Midjourneymidjourney.md
Leonardoleonardo.md
Ideogramideogram.md
Replicatereplicate.md
Stable Diffusionstable-diffusion.md

Core Rules

1. Resolve aliases to official model IDs first

Community names shift quickly. Before calling an API, map the nickname to the provider model ID.

Community labelOfficial model ID to try firstNotes
Nano Bananagemini-2.5-flash-image-previewCommon nickname, not an official Google model ID
Nano Banana 2 / ProVerify provider docsUsually a provider preset over Gemini image models
GPT Image 1.5gpt-image-1.5Current OpenAI high-tier image model
GPT Image mini / iMinigpt-image-1-miniBudget/faster OpenAI variant
FLUX 2 Pro / Maxflux-pro / flux-ultraMany platforms rename these SKUs

2. Pick models by task, not by hype

TaskFirst choiceBackup
Exact text in imagegpt-image-1.5Ideogram
Multi-turn editsgemini-2.5-flash-image-previewflux-kontext-pro
Photoreal hero shotsimagen-4.0-ultra-generate-001flux-ultra
Fast low-cost draftsgpt-image-1-miniimagen-4.0-fast-generate-001
Character/product consistencyflux-kontext-maxgpt-image-1.5 with references
Local no-API workflowsflux-schnellSDXL

3. Use benchmark tables as dated snapshots

Benchmarks drift weekly. Use benchmarks-2026.md as a starting point, then recheck current rankings when quality is critical.

4. Draft cheap, finish expensive

Start with 1-4 low-cost drafts, pick one, then upscale or rerender only the winner.

5. Keep a fallback chain

If the preferred model is unavailable, fallback by tier: 1) same provider lower tier, 2) cross-provider equivalent, 3) local/open model.

6. Treat DALL-E as legacy

OpenAI lists DALL-E 2/3 as legacy. Do not use them as default for new projects.

Common Traps

  • Using vendor nicknames as model IDs -> API errors and wasted retries
  • Assuming "Nano Banana Pro" or "FLUX 2" are universal IDs -> provider mismatch
  • Copying old DALL-E prompt habits -> weaker output vs modern GPT/Gemini image models
  • Comparing text-to-image and image-editing scores as if they were the same benchmark
  • Optimizing every draft at max quality -> cost spikes without quality gain

Security & Privacy

Data that leaves your machine:

  • Prompt text
  • Reference images when editing or style matching

Data that stays local:

  • Provider preferences in ~/image-generation/memory.md
  • Optional local history file

This skill does NOT:

  • Store API keys
  • Upload files outside chosen provider requests
  • Persist generated images unless user asks to save them

External Endpoints

ProviderEndpointData SentPurpose
OpenAIapi.openai.comPrompt text, optional input imagesGPT Image generation/editing
Google Gemini APIgenerativelanguage.googleapis.comPrompt text, optional input imagesGemini image generation/editing
Google Vertex AIaiplatform.googleapis.comPrompt text, optional input imagesImagen 4 generation
Black Forest Labsapi.bfl.aiPrompt text, optional input imagesFLUX generation/editing
Replicateapi.replicate.comPrompt text, optional input imagesHosted third-party image models
Midjourneydiscord.comPrompt textMidjourney generation via Discord workflows
Leonardocloud.leonardo.aiPrompt text, optional input imagesLeonardo generation/editing
Ideogramapi.ideogram.aiPrompt textTypography-focused image generation

No other data is sent externally.

Migration

If upgrading from a previous version, read migration.md before updating local memory structure.

Trust

This skill may send prompts and reference images to third-party AI providers. Only install if you trust those providers with your content.

Related Skills

Install with clawhub install <slug> if user confirms:

  • image-edit - Specialized inpainting, outpainting, and mask workflows
  • video-generation - Convert image concepts into video pipelines
  • colors - Build palettes for visual consistency across assets
  • ffmpeg - Post-process image sequences and exports

Feedback

  • If useful: clawhub star image-generation
  • Stay updated: clawhub sync

适合场景

01

文本生成图片

02

图片风格化

03

产品图和创意图

04

需要 FLUX 模型时

能力概览

能力 1

调用 FLUX 图像模型

能力 2

支持文本生图和图像改写

能力 3

覆盖 LoRA 或风格适配

能力 4

适合创意视觉生成

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

72.3%
按下载量换算56,401

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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